6e64d89410
tools/target_dem_fuzzer: Limit max blocks
...
With a IO block size of 1 byte potentially megabytes are quite slow to read, thus
limit the number
Fixes: 26511/clusterfuzz-testcase-minimized-ffmpeg_dem_NUV_fuzzer-5679249073373184
Fixes: 26517/clusterfuzz-testcase-minimized-ffmpeg_dem_XMV_fuzzer-6316634501021696
Fixes: 26518/clusterfuzz-testcase-minimized-ffmpeg_dem_WSVQA_fuzzer-485568285324083
Fixes: 26525/clusterfuzz-testcase-minimized-ffmpeg_dem_MSNWC_TCP_fuzzer-5121987011411968
Fixes: 26538/clusterfuzz-testcase-minimized-ffmpeg_dem_DHAV_fuzzer-5441800598454272
Fixes: OOM
Fixes: Timeout
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
c5b8f2321c
tools/target_dec_fuzzer: Adjust threshold for opus
...
Fixes: Timeout (12sec -> 3sec)
Fixes: 24549/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_LIBOPUS_fuzzer-6211170349088768
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
3e4214109a
tools/target_dec_fuzzer: remove calls to avcodec_register*()
...
They are no longer needed.
Signed-off-by: James Almer <jamrial@gmail.com>
4 years ago
a8a1a58af3
tools/target_dem_fuzzer: switch to the iterate API
...
Signed-off-by: James Almer <jamrial@gmail.com>
4 years ago
c0c6b68ddb
tools/target_dec_fuzzer: assume that discarded audio packets produced max samples
...
We do not know how many samples these produce as its not exported.
Alternatively we could export that but as long as its not we better
assume its more than 0 as otherwise the thresholds would not work
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
c062dd74d7
tools/target_dec_fuzzer: Correct maxsamples_per_frame if maxsamples has been changed
...
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
af701196ec
tools/target_dem_fuzzer: Set format independent of c
...
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
d40679d89c
Add support for building fuzzer tools for an individual demuxer
...
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
ad2546e3b3
dnn/native: add native support for dense
...
Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
4 years ago
5dae33bb39
tools/target_dec_fuzzer: Adjust VQA threshold
...
Fixes: Timeout (169sec -> 9sec)
Fixes: 23745/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_VQA_fuzzer-5638172179693568
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
e3af2a0756
tools:target_dem_fuzzer: Split into a fuzzer fuzzing at the protocol level and one fuzzing a fixed demuxer input
...
This should improve coverage and should improve the efficiency of seed files
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
a12864938d
tools/target_dec_fuzzer: Adjust threshold for WMV3IMAGE
...
Fixes: Timeout (1131sec -> 1sec)
Fixes: 24727/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_WMV3IMAGE_fuzzer-5754167793287168
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
3477feb643
dnn_backend_native_layer_mathbinary: add floormod support
...
Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
4 years ago
d08c3f56ec
tools/target_dec_fuzzer: Adjust threshold for DST
...
Fixes: Timeout (too long -> 3sec)
Fixes: 24239/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_DST_fuzzer-5189061015502848
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Reviewed-by: Peter Ross <pross@xvid.org>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
4ed6bca4ae
dnn_backend_native_layer_mathunary: add round support
...
Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
Reviewed-by: Guo, Yejun <yejun.guo@intel.com>
4 years ago
4b7189848f
tools/target_dec_fuzzer: Adjust threshold for AGM
...
Fixes: Timeout (142sec -> 2sec)
Fixes: 24426/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_AGM_fuzzer-5639724379930624
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
91efc41a69
dnn/native: add native support for avg_pool
...
Not support pooling strides in channel dimension yet.
Signed-off-by: Ting Fu <ting.fu@intel.com>
Reviewed-by: Guo, Yejun <yejun.guo@intel.com>
4 years ago
fab00b0ae0
dnn_backend_native_layer_mathunary: add floor support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import os
import numpy as np
import imageio
from tensorflow.python.framework import graph_util
name = 'floor'
pb_file_path = os.getcwd()
if not os.path.exists(pb_file_path+'/{}_savemodel/'.format(name)):
os.mkdir(pb_file_path+'/{}_savemodel/'.format(name))
with tf.Session(graph=tf.Graph()) as sess:
in_img = imageio.imread('detection.jpg')
in_img = in_img.astype(np.float32)
in_data = in_img[np.newaxis, :]
input_x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
y_ = tf.math.floor(input_x*255)/255
y = tf.identity(y_, name='dnn_out')
sess.run(tf.global_variables_initializer())
constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
with tf.gfile.FastGFile(pb_file_path+'/{}_savemodel/model.pb'.format(name), mode='wb') as f:
f.write(constant_graph.SerializeToString())
print("model.pb generated, please in ffmpeg path use\n \n \
python tools/python/convert.py {}_savemodel/model.pb --outdir={}_savemodel/ \n \nto generate model.model\n".format(name,name))
output = sess.run(y, feed_dict={ input_x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
print("To verify, please ffmpeg path use\n \n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow -f framemd5 {}_savemodel/tensorflow_out.md5\n \
or\n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow {}_savemodel/out_tensorflow.jpg\n \nto generate output result of tensorflow model\n".format(name, name, name, name))
print("To verify, please ffmpeg path use\n \n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native -f framemd5 {}_savemodel/native_out.md5\n \
or \n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native {}_savemodel/out_native.jpg\n \nto generate output result of native model\n".format(name, name, name, name))
Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
4 years ago
9fbdd5454b
dnn_backend_native_layer_mathunary: add ceil support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import os
import numpy as np
import imageio
from tensorflow.python.framework import graph_util
name = 'ceil'
pb_file_path = os.getcwd()
if not os.path.exists(pb_file_path+'/{}_savemodel/'.format(name)):
os.mkdir(pb_file_path+'/{}_savemodel/'.format(name))
with tf.Session(graph=tf.Graph()) as sess:
in_img = imageio.imread('detection.jpg')
in_img = in_img.astype(np.float32)
in_data = in_img[np.newaxis, :]
input_x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
y = tf.math.ceil( input_x, name='dnn_out')
sess.run(tf.global_variables_initializer())
constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
with tf.gfile.FastGFile(pb_file_path+'/{}_savemodel/model.pb'.format(name), mode='wb') as f:
f.write(constant_graph.SerializeToString())
print("model.pb generated, please in ffmpeg path use\n \n \
python tools/python/convert.py ceil_savemodel/model.pb --outdir=ceil_savemodel/ \n \n \
to generate model.model\n")
output = sess.run(y, feed_dict={ input_x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
print("To verify, please ffmpeg path use\n \n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model=ceil_savemodel/model.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow -f framemd5 ceil_savemodel/tensorflow_out.md5\n \n \
to generate output result of tensorflow model\n")
print("To verify, please ffmpeg path use\n \n \
./ffmpeg -i detection.jpg -vf format=rgb24,dnn_processing=model=ceil_savemodel/model.model:input=dnn_in:output=dnn_out:dnn_backend=native -f framemd5 ceil_savemodel/native_out.md5\n \n \
to generate output result of native model\n")
Signed-off-by: Mingyu Yin <mingyu.yin@intel.com>
Reviewed-by: Guo, Yejun <yejun.guo@intel.com>
4 years ago
c0cdeea0ee
dnn_backend_native_layer_mathunary: add atanh support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
please uncomment the part you want to test
x_sinh_1 = tf.sinh(x)
x_out = tf.divide(x_sinh_1, 1.176) # sinh(1.0)
x_cosh_1 = tf.cosh(x)
x_out = tf.divide(x_cosh_1, 1.55) # cosh(1.0)
x_tanh_1 = tf.tanh(x)
x__out = tf.divide(x_tanh_1, 0.77) # tanh(1.0)
x_asinh_1 = tf.asinh(x)
x_out = tf.divide(x_asinh_1, 0.89) # asinh(1.0/1.1)
x_acosh_1 = tf.add(x, 1.1)
x_acosh_2 = tf.acosh(x_acosh_1) # accept (1, inf)
x_out = tf.divide(x_acosh_2, 1.4) # acosh(2.1)
x_atanh_1 = tf.divide(x, 1.1)
x_atanh_2 = tf.atanh(x_atanh_1) # accept (-1, 1)
x_out = tf.divide(x_atanh_2, 1.55) # atanhh(1.0/1.1)
y = tf.identity(x_out, name='dnn_out') #please only preserve the x_out you want to test
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
cd2e3a864d
dnn_backend_native_layer_mathunary: add acosh support
...
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
9d14b38d9d
dnn_backend_native_layer_mathunary: add asinh support
...
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
ea71e731f4
dnn_backend_native_layer_mathunary: add tanh support
...
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
62fc7e3035
dnn_backend_native_layer_mathunary: add cosh support
...
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
91b4037101
dnn_backend_native_layer_mathunary: add sinh support
...
Signed-off-by: Ting Fu <ting.fu@intel.com>
4 years ago
13f5613e68
dnn_backend_native_layer_mathunary: add atan support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.atan(x)
x2 = tf.divide(x1, 3.1416/4) # pi/4
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
461485feac
dnn_backend_native_layer_mathunary: add acos support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.acos(x)
x2 = tf.divide(x1, 3.1416/2) # pi/2
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
486c0c419d
dnn_backend_native_layer_mathunary: add asin support
...
It can be tested with the model generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.asin(x)
x2 = tf.divide(x1, 3.1416/2) # pi/2
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
0b182ff66d
tools/target_dec_fuzzer: Adjust threshold for lagarith
...
Fixes: Timeout (3minute 49 sec -> 3sec)
Fixes: 22020/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_LAGARITH_fuzzer-5708544679870464
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
d3747f4431
tools/target_dem_fuzzer: Use file extensions listed in input formats
...
This should make it easier for the fuzzer to fuzz formats being detected only by
file extension and thus increase coverage
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
4 years ago
22d0860c13
dnn_backend_native_layer_mathunary: add tan support
...
It can be tested with the model generated with below python scripy
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 0.78)
x2 = tf.tan(x1)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
88fb494f42
dnn_backend_native_layer_mathunary: add cos support
...
It can be tested with the model generated with below python scripy
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 1.5)
x2 = tf.cos(x1)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
0b6d3f0d83
dnn_backend_native_layer_mathunary: add sin support
...
It can be tested with the model file generated with below python scripy:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.multiply(x, 3.14)
x2 = tf.sin(x1)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo Yejun <yejun.guo@intel.com>
4 years ago
3371d0611f
tools/target_dec_fuzzer: enable mjpeg for tiff or tdsc
...
This is needed for fuzzing tiff/tdsc and should increase coverage
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
3e651eeac4
tools/target_dem_fuzzer: Implement AVSEEK_SIZE
...
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
f73cc61bf5
dnn_backend_native_layer_mathunary: add abs support
...
more math unary operations will be added here
It can be tested with the model file generated with below python scripy:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpeg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.subtract(x, 0.5)
x2 = tf.abs(x1)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
5 years ago
6d4fdb4f5a
tools/target_dec_fuzzer: Adjust max_pixels for AV_CODEC_ID_HAP
...
Fixes: Timeout (170sec -> 6sec)
Fixes: 20956/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_HAP_fuzzer-5713643025203200
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
d6824ef905
tools/target_dec_fuzzer: Reduce maxpixels for HEVC
...
high resolutions with only small blocks appear to be rather
slow with the fuzzer + sanitizers.
A solution which makes this run faster is welcome.
Fixes: Timeout (did not wait -> 17sec)
Fixes: 21006/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_HEVC_fuzzer-6002552539971584
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
05d364dccc
tools/target_dec_fuzzer: Do not test AV_CODEC_FLAG2_FAST with AV_CODEC_ID_H264
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This combination skips allocating large padding which can read out of array
Fixes: 20978/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_H264_fuzzer-5746381832847360
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
ea980d4162
fate: add tests for h264 and vp9 video enc parameters export
5 years ago
bf80725352
lavc: rename bsf.h to bsf_internal.h
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This will allow adding a public header named bsf.h
5 years ago
4f54982773
tools/target_dec_fuzzer: Adjust threshold for PNG and APNG
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Fixes: Timeout (84sec -> 2sec)
Fixes: 21127/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_APNG_fuzzer-5098412367413248
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
71e28c5422
dnn/native: add native support for minimum
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it can be tested with model file generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.minimum(0.7, x)
x2 = tf.maximum(x1, 0.4)
y = tf.identity(x2, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
5 years ago
d817b57d36
tools: fix const specifier for AVInputFormat
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Signed-off-by: Josh de Kock <josh@itanimul.li>
5 years ago
8ce9d88f93
dnn/native: add native support for divide
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it can be tested with model file generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
z1 = 2 / x
z2 = 1 / z1
z3 = z2 / 0.25 + 0.3
z4 = z3 - x * 1.5 - 0.3
y = tf.identity(z4, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
5 years ago
ef79408e97
dnn/native: add native support for 'mul'
...
it can be tested with model file generated from above python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
z1 = 0.5 + 0.3 * x
z2 = z1 * 4
z3 = z2 - x - 2.0
y = tf.identity(z3, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
5 years ago
6aa7e07e7c
dnn/native: add native support for 'add'
...
It can be tested with the model file generated with below python script:
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
z1 = 0.039 + x
z2 = x + 0.042
z3 = z1 + z2
z4 = z3 - 0.381
z5 = z4 - x
y = tf.math.maximum(z5, 0.0, name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)
print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
5 years ago
39962072a8
tools: stop using deprecated av_codec_next()
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Signed-off-by: Josh de Kock <josh@itanimul.li>
5 years ago
2db37bf4cd
tools/target_dec_fuzzer: Adjust threshold for zerocodec
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Fixes: Timeout (147sec -> 1sec)
Fixes: 20764/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_ZEROCODEC_fuzzer-5068274603917312
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
8dee1d7a30
tools/target_dec_fuzzer: Adjust threshold for screenpresso
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Fixes: Timeout (332 -> 21 sec)
Fixes: 20280/clusterfuzz-testcase-minimized-ffmpeg_AV_CODEC_ID_SCREENPRESSO_fuzzer-6238663432470528
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
5 years ago
Michael Niedermayer
James Almer
Mingyu Yin
Ting Fu
Anton Khirnov
Guo, Yejun
Josh de Kock